GSD-2020-26270

Vulnerability from gsd - Updated: 2023-12-13 01:22
Details
In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.
Aliases
Aliases
CVE-2020-26270
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{
  "GSD": {
    "alias": "CVE-2020-26270",
    "description": "In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.",
    "id": "GSD-2020-26270",
    "references": [
      "https://www.suse.com/security/cve/CVE-2020-26270.html",
      "https://security.archlinux.org/CVE-2020-26270"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2020-26270"
      ],
      "details": "In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.",
      "id": "GSD-2020-26270",
      "modified": "2023-12-13T01:22:09.219444Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
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        "ID": "CVE-2020-26270",
        "STATE": "PUBLIC",
        "TITLE": "CHECK-fail in LSTM with zero-length input in TensorFlow"
      },
      "affects": {
        "vendor": {
          "vendor_data": [
            {
              "product": {
                "product_data": [
                  {
                    "product_name": "tensorflow",
                    "version": {
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                        },
                        {
                          "version_value": "\u003e= 2.2.0, \u003c 2.2.2"
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                          "version_value": "\u003e= 2.3.0, \u003c 2.3.2"
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            "value": "In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0."
          }
        ]
      },
      "impact": {
        "cvss": {
          "attackComplexity": "LOW",
          "attackVector": "LOCAL",
          "availabilityImpact": "LOW",
          "baseScore": 4.4,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "NONE",
          "integrityImpact": "LOW",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L",
          "version": "3.1"
        }
      },
      "problemtype": {
        "problemtype_data": [
          {
            "description": [
              {
                "lang": "eng",
                "value": "CWE-20 Improper Input Validation"
              }
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          }
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      },
      "references": {
        "reference_data": [
          {
            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m648-33qf-v3gp",
            "refsource": "CONFIRM",
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m648-33qf-v3gp"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3"
          }
        ]
      },
      "source": {
        "advisory": "GHSA-m648-33qf-v3gp",
        "discovery": "UNKNOWN"
      }
    },
    "gitlab.com": {
      "advisories": [
        {
          "affected_range": "(,1.15.5),[2.0.0,2.0.4),[2.1.0,2.1.3),[2.2.0,2.2.2),[2.3.0,2.3.2)",
          "affected_versions": "All versions before 1.15.5, all versions starting from 2.0.0 before 2.0.4, all versions starting from 2.1.0 before 2.1.3, all versions starting from 2.2.0 before 2.2.2, all versions starting from 2.3.0 before 2.3.2",
          "cvss_v2": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L",
          "cwe_ids": [
            "CWE-1035",
            "CWE-20",
            "CWE-937"
          ],
          "date": "2020-12-14",
          "description": "In affected versions of TensorFlow running an `LSTM/GRU` model where the `LSTM/GRU` layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer.",
          "fixed_versions": [],
          "identifier": "CVE-2020-26270",
          "identifiers": [
            "CVE-2020-26270",
            "GHSA-m648-33qf-v3gp"
          ],
          "not_impacted": "",
          "package_slug": "maven/org.tensorflow/parentpom",
          "pubdate": "2020-12-10",
          "solution": "Unfortunately, there is no solution available yet.",
          "title": "Improper Input Validation",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2020-26270"
          ],
          "uuid": "01c64304-d2bb-4cb7-857c-14f9856d2137"
        },
        {
          "affected_range": "\u003c1.15.5||\u003e=2.0.0,\u003c2.0.4||\u003e=2.1.0,\u003c2.1.3||\u003e=2.2.0,\u003c2.2.2||\u003e=2.3.0,\u003c2.3.2",
          "affected_versions": "All versions before 1.15.5, all versions starting from 2.0.0 before 2.0.4, all versions starting from 2.1.0 before 2.1.3, all versions starting from 2.2.0 before 2.2.2, all versions starting from 2.3.0 before 2.3.2",
          "cvss_v2": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L",
          "cwe_ids": [
            "CWE-1035",
            "CWE-20",
            "CWE-937"
          ],
          "date": "2021-01-07",
          "description": "In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.",
          "fixed_versions": [
            "1.15.5",
            "2.0.4",
            "2.1.3",
            "2.2.2",
            "2.3.2"
          ],
          "identifier": "CVE-2020-26270",
          "identifiers": [
            "GHSA-m648-33qf-v3gp",
            "CVE-2020-26270"
          ],
          "not_impacted": "All versions starting from 1.15.5 before 2.0.0, all versions starting from 2.0.4 before 2.1.0, all versions starting from 2.1.3 before 2.2.0, all versions starting from 2.2.2 before 2.3.0, all versions starting from 2.3.2",
          "package_slug": "pypi/tensorflow-cpu",
          "pubdate": "2020-12-10",
          "solution": "Upgrade to versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or above.",
          "title": "Improper Input Validation",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m648-33qf-v3gp",
            "https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3",
            "https://nvd.nist.gov/vuln/detail/CVE-2020-26270",
            "https://github.com/advisories/GHSA-m648-33qf-v3gp"
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        },
        {
          "affected_range": "\u003c1.15.5||\u003e=2.0.0,\u003c2.0.4||\u003e=2.1.0,\u003c2.1.3||\u003e=2.2.0,\u003c2.2.2||\u003e=2.3.0,\u003c2.3.2",
          "affected_versions": "All versions before 1.15.5, all versions starting from 2.0.0 before 2.0.4, all versions starting from 2.1.0 before 2.1.3, all versions starting from 2.2.0 before 2.2.2, all versions starting from 2.3.0 before 2.3.2",
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          "cwe_ids": [
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            "CWE-20",
            "CWE-937"
          ],
          "date": "2021-01-07",
          "description": "In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.",
          "fixed_versions": [
            "1.15.5",
            "2.0.4",
            "2.1.3",
            "2.2.2",
            "2.3.2"
          ],
          "identifier": "CVE-2020-26270",
          "identifiers": [
            "GHSA-m648-33qf-v3gp",
            "CVE-2020-26270"
          ],
          "not_impacted": "All versions starting from 1.15.5 before 2.0.0, all versions starting from 2.0.4 before 2.1.0, all versions starting from 2.1.3 before 2.2.0, all versions starting from 2.2.2 before 2.3.0, all versions starting from 2.3.2",
          "package_slug": "pypi/tensorflow-gpu",
          "pubdate": "2020-12-10",
          "solution": "Upgrade to versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or above.",
          "title": "Improper Input Validation",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m648-33qf-v3gp",
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            "https://nvd.nist.gov/vuln/detail/CVE-2020-26270",
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          "uuid": "c688062d-6581-4b89-99c3-79f77642fa40"
        },
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          "affected_range": "\u003c1.15.5||\u003e=2.0.0,\u003c2.0.4||\u003e=2.1.0,\u003c2.1.3||\u003e=2.2.0,\u003c2.2.2||\u003e=2.3.0,\u003c2.3.2",
          "affected_versions": "All versions before 1.15.5, all versions starting from 2.0.0 before 2.0.4, all versions starting from 2.1.0 before 2.1.3, all versions starting from 2.2.0 before 2.2.2, all versions starting from 2.3.0 before 2.3.2",
          "cvss_v2": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
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            "CWE-937"
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          "description": "In affected versions of TensorFlow running an `LSTM/GRU` model where the `LSTM/GRU` layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer.",
          "fixed_versions": [
            "2.4.0"
          ],
          "identifier": "CVE-2020-26270",
          "identifiers": [
            "CVE-2020-26270",
            "GHSA-m648-33qf-v3gp"
          ],
          "not_impacted": "All versions starting from 1.15.5 before 2.0.0, all versions starting from 2.0.4 before 2.1.0, all versions starting from 2.1.3 before 2.2.0, all versions starting from 2.2.2 before 2.3.0, all versions starting from 2.3.2",
          "package_slug": "pypi/tensorflow",
          "pubdate": "2020-12-10",
          "solution": "Upgrade to version 2.4.0 or above.",
          "title": "Improper Input Validation",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2020-26270"
          ],
          "uuid": "d15773ea-4352-4f61-b82c-34b32beef425"
        }
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            "accessComplexity": "LOW",
            "accessVector": "LOCAL",
            "authentication": "NONE",
            "availabilityImpact": "PARTIAL",
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            "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
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      },
      "lastModifiedDate": "2020-12-14T17:33Z",
      "publishedDate": "2020-12-10T23:15Z"
    }
  }
}


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  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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